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• A very useful new statistical method
  Antonio J Cunha
  Published on: 22 March 2016

• Published on: 22 March 2016

  A very useful new statistical method

  • Antonio J Cunha, MD, PhD

  Dear Editor,

  The article by Akobeng and Heller (1) is very interesting indeed and seems to be very useful. They suggest that using the PIN-ER-t (population impact number of eliminating a risk factor over a period of time), which is defined as the potential number of disease events prevented in a population over the next t years by eliminating a risk factor (2), allows numbers to be communicated in a more friend...

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  Dear Editor,

  The article by Akobeng and Heller (1) is very interesting indeed and seems to be very useful. They suggest that using the PIN-ER-t (population impact number of eliminating a risk factor over a period of time), which is defined as the potential number of disease events prevented in a population over the next t years by eliminating a risk factor (2), allows numbers to be communicated in a more friendly way to show the impact of risk factors for the disease in a population to both decision makers and general public (1). I used their examples, presented in their article, with some of my graduate and undergraduate students and they indeed found this way of expressing the impact of risk factors much more friendly. Thus, it seems that not only police makers and the general public may benefit from this approach. My students only found a little trick to use ´no breast feeding´ as a risk factor. In fact, it is possible to phrase PIN-ER-t as the potential number of disease events prevented in a population over the next t years by introducing a preventive factor, in this case breast feeding. In any case, this measure might be very useful, in special in developing countries, where resources in general are limited. It is possible to calculate, using the PIN-ER-t numbers obtained, the amount of resources that could be saved if a risk factor is eliminated or its effect minimized. For example, knowing the number of asthma cases that could be prevented, let say, in a year, and by knowing the prevalence of the different levels of severity of this disease in children (mild, moderate and severe) in a certain setting, as well as how much resources are spent by families and the health system with the disease (medications, hospitalization etc.), it is possible to calculate how much resources on average would be saved. With the epidemiologic transition, more and more chronic diseases, such as asthma and obesity, have greater impact in transition countries with large populations such as mine. I wonder whether the authors thought about improving the PIN-ER-t measure allowing it to be calculated when two or more diseases coexist in the same individual, for instance, asthma and obesity. Also, how would it be calculated if those diseases may interact or modify each other effect as it seems to happen in this case. Anyway, I would like to congratulate the authors for this very interesting article and the Editors for publishing it.

  (1) Akobeng AK, Heller RF. Assessing the population impact of low rates of breast feeding on asthma, coeliac disease and obesity: the use of a new statistical method. Arch Dis Child 2007; 92: 483-485

  (2) Heller RF, Buchan I, Edwards R, et al. Communicating risk at the population level: application of population impact numbers. BMJ 2005;327:1162-5

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  Conflict of Interest:
  None declared.

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